Meeting Banner
Abstract #1794

Resting-state functional connectivity predicts subsequent pain-related threat learning

Balint Kincses1,2, Katarina Forkmann1, Katharina Schmidt1, Ulrike Bingel1, and Tamas Spisak2
1Bingel-laboratory, Department of Neurology, University Hospital Essen, Essen, Germany, 2Laboratory of Predictive NeuroImaging, Institute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany


Fear conditioning has a role in anxiety-disorders and the neurobiological correlates of it are not yet well understood. Therefore, we trained a machine learning predictive model on individual functional resting state connectivity data to predict the emotional aspects of fear conditioning. The model was found to predict individual pain-related threat learning measured by the change of valence with an explained variance of 24%-41%. These results highlight the potential of machine learning to enhance our understanding of fear conditioning.

This abstract and the presentation materials are available to members only; a login is required.

Join Here